Optimization Algorithm for Urban Traffic Flow Based on Complex Networks

This article points out the seriousness and urgency of urban traffic congestion, and the shortcomings of existing research in solving this problem. In order to make up for these shortcomings, based on the complex network theory, this study deeply analyzes the urban traffic flow and puts forward the corresponding optimization strategies. In terms of methods, this article adopts the historical data of the actual urban traffic system, constructs a detailed experimental scene, and designs an advanced optimization algorithm to realize the optimization of traffic flow. Through a lot of experiments and simulations, the parameters of the algorithm are constantly adjusted to find the best optimization scheme. The results show that the optimized model can significantly improve the road capacity and reduce traffic congestion and waiting time. In peak hours and special events, the optimization effect is particularly significant. At the same time, the sensitivity and robustness of the model are deeply analyzed, which proves the stability of the model under different parameter settings and disturbances. By optimizing the control strategy of traffic lights, the driving route of vehicles and the speed limit, this method can effectively alleviate the urban traffic congestion problem and improve the overall efficiency of the traffic system.